My entire life, I thought I was going to be a Doctor just like my father.
 
Then in 2017, I realized it wasn't my passion.
 
So, I decided to end my pre-medicine college track.
 
But, before I could, I had to have a plan.
 
My dad grew his medicine practice by building relationships and grow by word of mouth.
 
These same relationships he built were the foundation for me to seek help and learn about other career paths.
 
So, I started calling his network.
 
The second call I made was to his financial planner, Timmy.
 
Timmy taught me that there's 3 things everybody thinks about before they fall asleep.
 
1st: Did I hurt anyone today? If so, you can talk to someone about that.
 
2nd: Am I healthy? If not, you can call your doctor tomorrow - that's my Dad.
 
3rd: Have I made the right financial decisions for my family? That's where I come in.
 
I'm okay with batting 3rd in that lineup.
 
Since that day, I've spent my time simplifying financial decisions for my clients.
 
How I can help you:

➡️Review every year because life happens and things change
➡️Feel confident to make difficult financial decisions
➡️Develop a simple, implementable financial plan
➡️Hold you accountable to your goals

My results:

➡️The best 1st year my agency has ever seen in its 130+ year history
➡️Rookie of the year 2021
➡️New Advisor of the year 2021
➡️Over 100 households (and counting) receiving my help & expertise

If you want to learn more about how I help my clients and see if we’re a fit, you can schedule on my calendar HERE👇🏼

Calendly.com/sallavanti/intro

Mando Sallavanti III

Build generational wealth without the money stress | Financial Advisor for Big Tech (Paycom, Oracle, Salesforce) | Top 25 MassMutual Financial Advisor (2024)

You closed $4M in deals this year. You hit President's Club. 

You're making $500K... Why's your bank account look the same as 3 years ago?

Let me guess:

→ $80K commission check hit last month - already gone
→ RSUs vesting quarterly, no idea if you should sell
→ Owed $40K in taxes you weren't expecting
→ Looking at houses you can't tell if you can afford
→ Spouse is stressed about money even though you're crushing quota
→ You're one bad quarter away from serious financial stress

You're a B2B Sales Leader at a high-growth tech company.
You close seven-figure deals for your company.
You advise C-suite executives on complex buying decisions.

But your own finances are in total chaos.

Here's why:

Traditional financial advice doesn't work for enterprise sales.

"Just save 20% and max your 401k" doesn't mean anything when:

Your income swings $50K month-to-month
You have RSUs, ESPP, commission, or bonuses all hitting at different times
Your "income" includes stock that might be up 30% or down 20%
You're taxed at rates that nobody explains properly

You don't need a financial advisor who works with "high earners."

You need someone who works with sales leaders who live in your world.

That's us.

We work with Sales Leaders at B2B SaaS and Tech companies.

Here's what we do:

Phase 1: Stop the Bleeding

→ Commission cash flow system (capture money before it disappears)
→ RSU strategy (minimize the tax hit or concentration when vested)
→ Protection planning (life, disability - so your family is covered)

Phase 2: Build the Buffer

→ Build emergency fund (handle slow quarters without panic)
→ Automate commission capture (money builds wealth before spending)
→ Know what you can actually afford (house, cars, private school - no guessing)

Phase 3: Build Real Wealth

→ Diversify beyond company stock (systematic selling, no emotion)
→ Tax planning with your CPA (keep more of what you earn within your control)
→ Build multiple income streams (not 100% dependent on quota)

The outcome we plan for?

You're not just making money. 
You're keeping it.

You're not just hitting quota. 
You're building generational wealth.

You're not stressed about the next deal. 
You have OPTIONS.

THAT is your Freedom Path.

If you're crushing quota and tired of feeling broke, let's fix that.

Message me and tell me to get started!

Mando Sallavanti III, CFP®, CEPA, ChFC®

🤖Data Scientist | Turning Raw Data into Money Generating Insights | Data-led Growth for Your Business 🚀

Freelance Data Scientist | ML Engineer | SQL | Python | Power BI | MLOps

Data analytics and Machine learning models built 5X faster - no quality compromise. Worked with 14 clients in 7 different industries in the last 3 years. Helped current company scale to $5M+ ARR. Featured TOP RATED PLUS talent on Upwork in 2025 with 100% job completion and satisfaction.

My Toolkit:
- Data analytics: Python, SQL, Excel
- ML Engineering: FastAPI, AWS, Streamlit, great_expectations
- Data visualization: PowerPoint, PowerBI, Plotly, Matplotlib
- Data modeling: Scikit-learn, TensorFlow, Keras
- MLOPs: CI/CD (GitHub Actions), Docker
- Additional tools: Notion, n8n, Canva, Git/GitHub

My Stats:
- 5-stars reviews on 99% of projects delivered.
- 100% Job Success Score for on-time, budget delivery.
- Helped scale currently business to $5M ARR with ATS analysis & Reporting.
- 1.5 years TOP RATER PLUS on Upwork.
- 1800 hours billed.
- $60k+ earned.

What You’ll Get Working With Me:
- A data analyst who is a real problem solver.
- Quick responses (within the hour on working hours)
- Clean, maintainable code and detailed documentation
- A clear “NO” if something isn’t feasible; no wasted time
- A well-crafted report or dashboard as per the requirements

My clients think:
- "Anas is great and highly knowledgeable. He is passionate about solving data science challenges and has helped me significantly streamline some of my processes, enabling better scalability.
- "Anas, was prompt and thorough and I would def use him again in the future."
- "Anas is great to work with. He made the job so fluid and his knowledge of data science makes him someone worth listening to. I’m glad I chose him for my small business. I’m looking forward to what’s coming next, and I would definitely hire him again."

Popular Clients & Products:
- Uhubs: Financial company based in London
- AllAboutGroup: Law recruitment firm based in London
- Growth Dynamics: Marketing and data strategist based in London.
- Adway: Tech and recruitment company based in Gotheborg, Sweden

About me:
- Football fan since I can remember (Real Madrid fan)
- Tennis lover and practitioner (one-handed backhand style)
- Mangas fan (One Piece, Naruto, Bleach)
- Travel addict (South Asia, Europe, Africa, America (soon))
- Reading is something I enjoy as much as coffee (oat latte fan recently)

-----

YouTube Channel
→ GO HERE: https://www.youtube.com/anas_riad

Request services via LinkedIn or Email below:
r.riadanas@gmail.com

Hire on Upwork:
https://www.upwork.com/freelancers/~0163377bf3029c7553

Anas Riad

Dear recruiters,

If you expect a Data Scientist to be an expert in:

→ Python for large-scale data analysis
→ Excel with complex financial-style reports
→ Pandas and NumPy on real, broken datasets
→ Heavy data cleaning and feature engineering
→ Git workflows, CI/CD, and automated testing
→ LLMs, prompt design, and applied AI use cases
→ Business KPIs, north-star metrics, and trade-offs
→ Clear storytelling with non-technical stakeholders
→ Dockerized environments and reproducible pipelines
→ Experiment tracking, model versioning, and rollbacks
→ Data pipelines touching cloud storage and warehouses
→ Regression, classification, and model selection at scale
→ Advanced SQL with messy joins and window functions
→ Exploratory analysis with Matplotlib, Plotly, and Seaborn
→ Probability theory, hypothesis testing, and A/B experiments
→ Bias–variance trade-offs and model performance monitoring

… you’re not hiring one 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁.
You’re describing an 𝗲𝗻𝘁𝗶𝗿𝗲 𝗱𝗮𝘁𝗮 𝗱𝗲𝗽𝗮𝗿𝘁𝗺𝗲𝗻𝘁.

PS: Post inspired by José Siles

📌 Follow Anas Riad for more content around data science

Data Scientist & BI Consultant @Adway • ML Engineer • YouTube @ Anas Riad

YouTube is still the BEST place to learn ML.

Most people still watch the wrong videos.

Here are 𝟭𝟮 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝘃𝗶𝗱𝗲𝗼𝘀 𝘁𝗼 𝗺𝗮𝘀𝘁𝗲𝗿 ML ⤵️ 

---

𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝗖𝗦𝟮𝟮𝟵: 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
 
The legendary starting point for ML.
Covers core theory, intuition, and key algorithms.

Video: https://lnkd.in/e-aJRQun
 
---

𝗔𝗹𝗹 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 𝗶𝗻 𝟮𝟮 𝗠𝗶𝗻𝘂𝘁𝗲𝘀

A fast, structured overview of all major ML concepts.
Great for building a mental map before going deeper.
 
Video: https://lnkd.in/exCP58F6
 
---

𝗠𝗟𝗢𝗽𝘀 𝗖𝗼𝘂𝗿𝘀𝗲 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀
 
Shows how ML actually works in real products.
Pipelines, deployment, monitoring, and production mindset.
 
Video: https://lnkd.in/erzM3b4F

---

𝗛𝗼𝘄 𝘁𝗼 𝗗𝗲𝗽𝗹𝗼𝘆 𝗠𝗟 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 (𝗙𝗮𝘀𝘁𝗔𝗣𝗜, 𝗗𝗼𝗰𝗸𝗲𝗿, 𝗔𝗪𝗦)
 
From trained model to live service.
A practical deployment walkthrough with modern tools.
 
Video: https://lnkd.in/e3JtcAZk

---

𝗦𝘁𝗲𝗮𝗹 𝗠𝘆 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲

Learn how to structure ML projects properly.
Clean folders, reproducibility, and real-world practices.
 
Video: https://lnkd.in/eds2Buq8

---

𝗘𝗻𝗱-𝘁𝗼-𝗘𝗻𝗱 𝗠𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻
 
A full ML project from start to finish.
Data prep, modeling, evaluation, and delivery.
 
Video: https://lnkd.in/ebx_dvtn

---

𝗠𝗟𝗢𝗽𝘀 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹 (𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗩𝗶𝗲𝘄𝗲𝗿 𝗦𝗲𝗻𝘁𝗶𝗺𝗲𝗻𝘁)
 
Build a real ML pipeline using real data.
Feature engineering, modeling, and orchestration.
 
Video: https://lnkd.in/e9_xVb-Z

---

𝗬𝗼𝘂 𝗪𝗶𝗹𝗹 𝗡𝗢𝗧 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗶𝗻 𝟯 𝗠𝗼𝗻𝘁𝗵𝘀
 
A reality check on learning machine learning.
Focuses on process, depth, and consistency.
 
Video: https://lnkd.in/eRqYhJWK

---

𝗘𝗻𝗱-𝘁𝗼-𝗘𝗻𝗱 𝗥𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻 𝗠𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁
 
A practical regression project walkthrough.
Covers evaluation, assumptions, trade-offs.
 
Video: https://lnkd.in/e2GEnb4N

---

𝗘𝘃𝗲𝗿𝘆 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱
 
A clear overview of common ML models.
 
Video: https://lnkd.in/eMW3YNKq

---

𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗚𝗿𝗮𝗱𝗲 𝗠𝗟 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹
 
Focus on building ML systems that last.
Code quality, deployment, and maintainability.
 
Video: https://lnkd.in/eXYhdxgt

---

𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀)
 
A simple introduction to ML definitions and concepts.
 
Video: https://lnkd.in/eT3qrGBt
 
---

📌 Save this for your next project.
♻️ Repost this to help your network in data.

90% of analysts use only 10% of Pandas.

Master these 10 operations. Level up instantly.

When I started learning data analysis,
I thought Pandas was “too big” to master.

Turns out… you only need the core.

Here are the operations I use almost daily:

• 𝗟𝗼𝗮𝗱 𝗱𝗮𝘁𝗮 → pd.read_csv()
• 𝗜𝗻𝘀𝗽𝗲𝗰𝘁 𝗾𝘂𝗶𝗰𝗸𝗹𝘆 → .head(), .info(), .describe()
• 𝗦𝗲𝗹𝗲𝗰𝘁 𝗰𝗼𝗹𝘂𝗺𝗻𝘀 → df[["col1","col2"]]
• 𝗙𝗶𝗹𝘁𝗲𝗿 𝗿𝗼𝘄𝘀 → df[df["col"] > value]
• 𝗚𝗿𝗼𝘂𝗽 & 𝗮𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 → .groupby().agg()
• 𝗖𝗿𝗲𝗮𝘁𝗲 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 → df["new"] = expression
• 𝗠𝗲𝗿𝗴𝗲 𝗱𝗮𝘁𝗮𝘀𝗲𝘁𝘀 → pd.merge()
• 𝗛𝗮𝗻𝗱𝗹𝗲 𝗺𝗶𝘀𝘀𝗶𝗻𝗴 𝘃𝗮𝗹𝘂𝗲𝘀 → .isna(), .fillna()
• 𝗦𝗼𝗿𝘁 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 → .sort_values()
• 𝗘𝘅𝗽𝗼𝗿𝘁 𝗰𝗹𝗲𝗮𝗻 𝗱𝗮𝘁𝗮 → .to_csv() or .to_excel()

That’s it.

If you can combine these properly, you can solve 80% of real-world problems.

The rest is practice and business thinking.

PS: Is Pandas your go-to library for data analytics?

📌 Follow Anas Riad for more content around data science

I was never supposed to become a Data Scientist.

Nothing about my path pointed there.

I tried medicine.
Then architecture.
Spent 5 years on a Master’s in industrial engineering.
Worked as a professional DJ at the same time.

Then I found data science.
Late. Unexpectedly.
And honestly… it made no sense.

I changed countries.
I doubted myself constantly.
I had to spend one full year just learning how to speak better.
Five years ago, I couldn’t even express myself properly in this language.

Now I work in data science.
And create content in that same language.

It wasn’t linear.
It wasn’t clean.
And the odds were clearly against me.

What made the difference wasn’t just Python or maths.

Being a good data scientist is not only technical.

It’s also:

→ Being reliable when things break
→ Understanding the business, not just the model
→ Thinking clearly when data is messy
→ Explaining results so people actually act
→ Saying “this approach failed” and learning fast

Yes, you still need:

→ Coding
→ Statistics
→ Probability
→ Solid fundamentals

But that’s only part of the picture.

What really helped me:

→ Perseverance
→ Belief (especially when confidence was low)
→ Hard work
→ Learning from the right people

Data scientists don’t all look the same.
And they don’t come from the same background.

If your path feels messy, slow, or “wrong”,
you might actually be building something stronger.

PS: Did you find your path on the 1st try?

80% of analyst tasks will automate.

Will you still be relevant in 2026?

⭐ Venkata Naga Sai Kumar Bysani and I broke this down simply  ⤵️ 

1️⃣ Work with AI, not against it
Copilot, Claude, automation tools. Use them well. Guide them. Validate outputs.

2️⃣ SQL alone won’t cut it anymore
Add Python. Learn ML basics. Understand how data pipelines work.

3️⃣ Understand the business deeply
Dashboards are easy. Translating numbers into revenue, risk, and strategy is rare.

4️⃣ Solve problems, not tickets
No one cares about the tool. They care about impact.

5️⃣ Build systems that run without you
Automate reports. Schedule pipelines. Create alerts. Sleep while your work runs.

6️⃣ Explain insights clearly
If leadership can’t understand it, it won’t matter.

7️⃣ Share your work publicly
Document what you’re learning. Visibility creates leverage.

-- -- -- 

The analyst role isn’t disappearing.
It’s evolving.

And the ones who adapt will win big in 2026.

💬 What’s your take?
Is the Data Analyst role shrinking or just becoming more strategic?

📌 Follow Venkata Naga Sai Kumar Bysani & Anas Riad for top-tier data content
♻️ Repost this post with your network to benefit

I made $70k on Upwork as a data scientist.
Not by luck. By rules I didn’t break.

Here are my 6 non-negotiables 👇

-- -- -- 

𝟭. 𝗚𝗲𝘁 𝘆𝗼𝘂𝗿 𝗳𝗶𝗿𝘀𝘁 𝟮–𝟯 𝗳𝗶𝘃𝗲-𝘀𝘁𝗮𝗿 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 𝗳𝗮𝘀𝘁

I started with people I already trusted.
Friends. Family. Warm intros.
Social proof changes everything.

-- -- -- 

𝟮. 𝗟𝗲𝗮𝗿𝗻 𝗵𝗼𝘄 𝘁𝗼 𝘀𝗲𝗮𝗿𝗰𝗵 𝗼𝗻 𝗨𝗽𝘄𝗼𝗿𝗸 𝗽𝗿𝗼𝗽𝗲𝗿𝗹𝘆

Most people apply to bad jobs. I filtered hard:

- Same-day jobs
- Fewer proposals
- Verified clients
- $100k+ spent
- 4.3⭐+ rating

Bad jobs drain energy. Good jobs compound.

-- -- -- 

𝟯. 𝗙𝗶𝗹𝘁𝗲𝗿 𝗰𝗹𝗶𝗲𝗻𝘁𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀

Skills matter less than people. I avoided:

- Vague requirements
- Unreal timelines
- “Quick task” language
- Budget pressure early

Good clients respect scope. Toxic ones don’t.

-- -- -- 

𝟰. 𝗪𝗿𝗶𝘁𝗲 𝗽𝗿𝗼𝗽𝗼𝘀𝗮𝗹𝘀 𝘁𝗵𝗮𝘁 𝗳𝗲𝗲𝗹 𝗵𝘂𝗺𝗮𝗻

No copy-paste. No essays.
Short. Clear. Specific. And often a Loom video.
Seeing your face builds trust faster than text.

-- -- -- 

𝟱. 𝗣𝗿𝗶𝗰𝗲 𝗯𝗮𝘀𝗲𝗱 𝗼𝗻 𝘃𝗮𝗹𝘂𝗲, 𝗻𝗼𝘁 𝗳𝗲𝗮𝗿

I raised rates as confidence grew.
Experience compounds. So should pricing.

-- -- -- 

𝟲. 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗽𝗿𝗲𝘀𝗲𝗻𝗰𝗲 𝗼𝘂𝘁𝘀𝗶𝗱𝗲 𝗨𝗽𝘄𝗼𝗿𝗸 (𝗵𝘂𝗴𝗲 𝗯𝗼𝗻𝘂𝘀)

YouTube + LinkedIn helped clients trust me faster.
They could see how I think. Not just what I claim.

-- -- -- 

Upwork wasn’t the magic.
Systems were.

PS: What’s been your biggest struggle with freelancing so far?

♻️ Repost if you found this post useful
📌 Follow Anas Riad for Data & ML content

Everyone wants to be an AI Engineer.
But not many want to master the foundations first.

Miguel Otero Pedrido a Senior ML Engineer, recently told me:
“AI engineering becomes easy when your MLE foundations are strong.”

Still, most people skip the basics like:
→ CI/CD pipelines
→ Feature engineering
→ Model experimentation & tracking
→ Deployment, monitoring & observability
→ Reproducibility (Docker, version control, etc.)

Then they open n8n,
build a few workflows,
and call themselves AI engineers.

I’m not here to tell anyone what to do.
But over the years, I’ve learned to tune out the hype and stick to my plan.

The AI engineers you admire on LinkedIn?

Most have 5+ years of experience in data science and ML engineering.
They didn’t shift into AI overnight.

Stop following the hype.
Start building your career the right way.

♻️ Repost if useful
📌 Follow for Data & ML content

taplio

The Battle

Mando Sallavanti III, CFP®, CEPA, ChFC®

Anas Riad

Followers

Posts

Engagements

Likes

Performance ScoreAnas Riad's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Mando Sallavanti III, CFP®, CEPA, ChFC®

Anas Riad

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Anas Riad's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreAnas Riad's LinkedIn Performance